4 papers
FoilDiff: A Hybrid Transformer Backbone for Diffusion-based Modelling of 2D Airfoil Flow Fields
Kenechukwu Ogbuagu, Sepehr Maleki, Giuseppe Bruni +1
The accurate prediction of flow fields around airfoils is crucial for aerodynamic design and optimisation. Computational Fluid Dynamics (CFD) models are effective but computational…
Physics-Informed Neural Networks for Industrial Gas Turbines: Recent Trends, Advancements and Challenges
Afila Ajithkumar Sophiya, Sepehr Maleki, Giuseppe Bruni +1
Physics-Informed Neural Networks (PINNs) have emerged as a promising computational framework for solving differential equations by integrating deep learning with physical constrain…
C(NN)FD -- Deep Learning Modelling of Multi-Stage Axial Compressors Aerodynamics
Giuseppe Bruni, Sepehr Maleki, Senthil K Krishnababu
The field of scientific machine learning and its applications to numerical analyses such as CFD has recently experienced a surge in interest. While its viability has been demonstra…
Deep learning modelling of manufacturing and build variations on multi-stage axial compressors aerodynamics
Giuseppe Bruni, Sepehr Maleki, Senthil K. Krishnababu
Applications of deep learning to physical simulations such as Computational Fluid Dynamics have recently experienced a surge in interest, and their viability has been demonstrated…