Standout Papers

Multi-fidelity deep neural network surrogate model for aerodynamic shape optimization 2020 2026 2022 2024224
  1. Multi-fidelity deep neural network surrogate model for aerodynamic shape optimization (2020)
    Xinshuai Zhang, Fangfang Xie et al. Computer Methods in Applied Mechanics and Engineering

Immediate Impact

25 standout
Sub-graph 1 of 12

Citing Papers

β-Variational autoencoders and transformers for reduced-order modelling of fluid flows
2024 Standout
Physics-informed Neural Networks (PINN) for computational solid mechanics: Numerical frameworks and applications
2024 Standout
2 intermediate papers

Works of Tingwei Ji being referenced

Data-driven nonlinear reduced-order modeling of unsteady fluid–structure interactions
2022
Multi-fidelity deep neural network surrogate model for aerodynamic shape optimization
2020 Standout
and 1 more

Author Peers

Author Last Decade Papers Cites
Tingwei Ji 276 189 204 27 504
Xinshuai Zhang 164 130 113 22 445
Jean‐Christophe Jouhaud 311 214 109 22 529
E. Andrés 119 98 85 19 502
Jun Tao 136 167 72 25 507
Mathieu Couplet 201 110 229 13 459
Marc Montagnac 247 154 93 19 430
Joël Brézillon 419 167 94 44 570
Kenneth Badcock 261 222 92 28 503
Eric Parish 378 138 364 24 569
Anıl Yıldırım 289 210 87 28 437

All Works

Loading papers...

Rankless by CCL
2026