Multiscale space–time fluid–structure interaction techniques
By Kenji Takizawa, Tayfun E. Tezduyar. 2011
301 citations recorded by the source corpus.
Subfields: Computational Mechanics, Computational Theory and Mathematics
View Paper: https://www.semanticscholar.org/paper/5081f75ccdb670e751f5d7532c764ae517f4a712
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Computational Mechanics
- Ming-Chen Hsu
- Yuri Bazilevs
- Kenji Takizawa
- Bradley Henicke
- Sergio R. Idelsohn
- Eugenio Oñate
- Tayfun E. Tezduyar
- Thomas J. R. Hughes
In Computational Theory and Mathematics
- Ming-Chen Hsu
- Yuri Bazilevs
- Bradley Henicke
- Kenji Takizawa
- Tayfun E. Tezduyar
- Jinhui Yan
- Qiming Zhu
- Zeliang Liu
Citations in the corpus
- Stabilized space–time computation of wind-turbine rotor aerodynamics (2011, methodology): “We compute the problem with the DSD/SST-DP-SUPS and DSD/SST-DP-VMST [63] techniques.”
- Machine learning for metal additive manufacturing: predicting temperature and melt pool fluid dynamics using physics-informed neural networks (2020, methodology): “A SciML framework for metal AM processes, which can accurately predict temperature, pressure, and velocity field without relying on big-data.”
- Possibilities of the particle finite element method for fluid–soil–structure interaction problems (2011, methodology): “Examples of 3-D analysis of FSI problems using ALE and space-time FEM are reported in [4,6,26,27,31,34,40].”