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YuanTong Gu
Researcher at Queensland University of Technology
Publications - 597
Citations - 15277
YuanTong Gu is an academic researcher from Queensland University of Technology. The author has contributed to research in topics: Finite element method & Meshfree methods. The author has an hindex of 52, co-authored 550 publications receiving 12583 citations. Previous affiliations of YuanTong Gu include Nanjing Medical University & National University of Singapore.
Papers
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A novel physics-informed neural networks approach (PINN-MT) to solve mass transfer in plant cells during drying
TL;DR: In this paper , the authors investigated the feasibility of PINNs' Automatic Differentiation (AD) to solve mass transfer and effectively predict cellular-level mass loss and subsequent moisture variations during low-temperature drying.
Unresolved CFD-DEM of sandstone-laden air flow in a clear channel
TL;DR: In this paper, an unresolved finite-volume and discrete-element method that is able to capture the interaction between the lagrangian particles and carrier fluid in a clear channel is investigated.
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Magnetic Convection Heat Transfer in an Open Ended Enclosure Filled with Paramagnetic Fluids
TL;DR: In this paper, numerical simulations of thermomagnetic convection of paramagnetic fluids placed in a micro-gravity condition (g nearly 0) and under a uniform vertical gradient magnetic field in an open ended square enclosure with ramp heating temperature condition applied on a vertical wall is investigated.
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Topological surface state: Universal catalytic descriptor in topological catalysis
Xiaoming Zhang,Lirong Wang,Minghang Li,Weizhen Meng,Yang Liu,Xue-Lin Dai,Guodong Liu,YuanTong Gu,Junxian Liu,Liangzhi Kou +9 more
TL;DR: In this paper , the authors identify topological surface state (TSS) density at the Fermi level can serve as the universal catalytic descriptor in the family of metal diborides, the materials hosting fantasying topological nodal-net states.
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Revolute Joint Approach to Model Joint Mechanism in Water-Filled Road Safety Barriers
TL;DR: This research probes a new technique to model joints in PWFB and presents two methods to model the joining mechanism, which will benefit PWFB research and allow road barrier designers better knowledge in developing the next generation of road safety structures.