From the 1 of 5 linked papers with an AI index.
5 papers
Variational Parameter Calibration with Physics-Aware Latent-Space Surrogates
Qiyao Zhou, Xujia Zhu, Pierre Joli +2
Forward and inverse modeling of parametric dynamical systems requires surrogate models that are not only accurate for state prediction, but also informative for parameter calibrati…
A New Paradigm for 3D Turbomachinery Design: Generative Diffusion Model Based Framework with Direct Geometry Encoding
Yingfan Geng, Jinhong Wang, Lazaros Papachristodoulou +2
The paper introduces a denoising diffusion generative model that directly learns 3D blade geometry coordinates to solve inverse design problems for centrifugal compressors, produci…
From Deterministic to Generative Deep Learning for Urban Air Quality Reconstruction from Sparse Observations
Abhishek A. Sabnis, Mihai Mitrea, Lya Lugon +5
Full-field reconstruction of air pollution is essential for evaluating pollution exposure and supporting public health decision-making. However, the complex interactions among poll…
Accurate identification and measurement of the precipitate area by two-stage deep neural networks in novel chromium-based alloys
Zeyu Xia, Kan Ma, Sibo Cheng +7
The performance of advanced materials for extreme environments is underpinned by their microstructure, including the size and distribution of reinforcing phases. Chromium-based sup…
A Probabilistic Approach to Wildfire Spread Prediction Using a Denoising Diffusion Surrogate Model
Wenbo Yu, Anirbit Ghosh, Tobias Sebastian Finn +3
Thanks to recent advances in generative AI, computers can now simulate realistic and complex natural processes. We apply this capability to predict how wildfires spread, a task mad…