J
Jian Zhao
Researcher at Monash University, Clayton campus
Publications - 328
Citations - 15640
Jian Zhao is an academic researcher from Monash University, Clayton campus. The author has contributed to research in topics: Rock mass classification & Wave propagation. The author has an hindex of 60, co-authored 316 publications receiving 11636 citations. Previous affiliations of Jian Zhao include École Polytechnique Fédérale de Lausanne & Indian Institute of Technology Delhi.
Papers
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SINOROCK2004 Paper 2B 05Identification of dynamic rock properties using a genetic algorithm
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Biological and Nonbiological Sources of Fluorescent Aerosol Particles in the Urban Atmosphere.
Siyao Yue,Linjie Li,Weiqi Xu,Jian Zhao,Hong Ren,Dongsheng Li,Ping Li,Qiang Zhang,Lianfang Wei,Qiaorong Xie,Xiaole Pan,Zifa Wang,Yele Sun,Pingqing Fu +13 more
TL;DR: Wang et al. as mentioned in this paper used a wideband integrated bioaerosol sensor (WIBS, 0.8-20 μm) with the measurements of typical biological matter and the compositions related to major nonbiological FAP.
Journal Article
Study on damage characteristics of rock mass under blasting load in ling'ao nuclear power station,guangdong province
TL;DR: Wang et al. as discussed by the authors used a hybrid LS-DYNA and FLAC3D scheme to study the damage zone size of rock mass under blasting, and the numerical simulation results agree well with the site monitoring results.
Journal Article
Fracture mechanism and experiment of infilled rock joints
Ling Shi,Mei Feng Cai,Jian Zhao +2 more
TL;DR: In this paper, a theoretical shear strength formula was obtained and the effects of normal stress and filling thickness on the failure of infilled rock joints were studied. But the influence of filling thickness is not obvious.
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A multiscale manifold method using particle representations of the physical domain
TL;DR: In this article, a new multiscale method is proposed using the numerical manifold method (NMM) and its micro extension particle manifold methods (PMM), which has an advantage over PMM in presenting the material's micro structure and failure description and also saves the computational resource by using NMM to present the macro part.