arXiv:2606. 24265v1 Announce Type: cross Abstract: Numerical simulations in industrial applications often require performing numerous high-precision computations parameterized by specific experimental conditions.
By Kazuto Ando, Rahul Bale, Akiyoshi Kuroda, Makoto Tsubokura
Numerical simulations in industrial applications often require performing numerous high-precision computations parameterized by specific experimental conditions. For instance, in vehicle body design, aerodynamic simulations are essential for evaluating the aerodynamic characteristics of various proposed body geometries.
arXiv:2606. 16587v1 Announce Type: cross Abstract: Designing spray nozzles requires predicting how geometry shapes transient two-phase breakup, but high-fidelity volume-of-fluid (VOF) simulations with adaptive mesh refinement (AMR) are too expensive for iterative design exploration.
By Julius H Ramlau, Friedrich Hastedt, Tolga Birdal, Ehecatl-Antonio del R\'io Chanona, Nausheen S Basha, Omar K Matar
arXiv:2606. 07724v1 Announce Type: new Abstract: High-fidelity computational fluid dynamics (CFD) is crucial to vehicle aerodynamic analysis, but its cost still constrains early-stage design exploration.
By Kangkang Qi, Huiyu Yang, Keqi Ding, Yunpeng Wang, Yuntian Chen, Yuanwei Bin, Rikui Zhang, Jianchun Wang
arXiv:2606. 29628v1 Announce Type: cross Abstract: In this paper, two novel data-driven models based on kriging and neural networks (NN) are proposed to predict pressure losses across perforated plates with circular perforations in turbulent flows.
By Shuai Li
In this paper, two novel data-driven models based on kriging and neural networks (NN) are proposed to predict pressure losses across perforated plates with circular perforations in turbulent flows. The models are developed using two sets of experimental data available in the literature.